A comparison of document clustering techniques

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A comparison of document clustering techniques (2000)

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by Michael Steinbach , George Karypis , Vipin Kumar

Venue:	In KDD Workshop on Text Mining
Citations:	612 - 27 self

BibTeX

@INPROCEEDINGS{Steinbach00acomparison,
    author = {Michael Steinbach and George Karypis and Vipin Kumar},
    title = {A comparison of document clustering techniques},
    booktitle = {In KDD Workshop on Text Mining},
    year = {2000}
}

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Abstract

This paper presents the results of an experimental study of some common document clustering techniques: agglomerative hierarchical clustering and K-means. (We used both a “standard” K-means algorithm and a “bisecting ” K-means algorithm.) Our results indicate that the bisecting K-means technique is better than the standard K-means approach and (somewhat surprisingly) as good or better than the hierarchical approaches that we tested.

Keyphrases

common document experimental study bisecting k-means algorithm agglomerative hierarchical clustering hierarchical approach standard k-means algorithm k-means technique standard k-means approach

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